Brain–Computer Interfaces - Index of

Non Invasive BCIs for Neuroprostheses Control of the Paralysed Hand 175
Fig. 2 General idea of a brain-switch. (a) Features of different classes (e.g., left hand, right hand
or feet MI) are usually separated by an optimal decision border. Introducing an additional threshold
a switch function can be designed. (b) LDA output of two types of MI during no MI and MI
does not really change from a period without MI to a period with MI. However, the
other class (class 2) does. A significant change can be seen. It is assumed that the
first case (class 1) is a very general case. This means that the classifier would also
select this class when no MI is performed. Therefore, this describes the non-control
state. Introducing an additional threshold into the class of the other MI pattern
(class 2), a switch function can be designed (control state). A control signal is only
triggered when the MI is recognized clearly enough to exceed the threshold. For the
BCI application (see Fig. 3), the grasp is divided into distinct phases (Fig. 3c, d),
e.g., hand open, hand close, hand open, hand relax (stimulation off). Whenever a
trigger signal is induced, the users’ hand is stimulated so that the current phase is
subsequently switched to the next grasp phase. If the end of the grasp sequence is
reached, a new cycle is started.
2.1 Patients
The first patient enrolled in the study, TS, is a 32 year old man who became
tetraplegic because of a traumatic spinal cord injury in April 1998. He has a complete
(ASIA A, described by the American Spinal Cord Injury Association, [30])
motor and sensory paralysis at the level of the 5th cervical spinal vertebra. Volitional